The goal of this research is to determine whether hospital financial performance is impacted by particular management accounting techniques, such as departmental revenue budgeting, specific costing, and departmental costing. We analyzed several sets of performance indicators for 146 hospitals whose management accounting adoption status is available. An outlier test was used to determine which data were outliers at the 0.1% significance level, and the results were then eliminated in order to see if any extremely outlier values (hospitals) were present for each indicator. To determine whether there were any noteworthy variations in the average values of the several performance measures, we employed a t-test (two-tailed probability). The results suggest that departmental revenue budgeting and departmental and specific costing improve hospital financial performance.

This study explores the intricate relationship between emotional cues present in food delivery app reviews, normative ratings, and reader engagement. Utilizing lexicon-based unsupervised machine learning, our aim is to identify eight distinct emotional states within user reviews sourced from the Google Play Store. Our primary goal is to understand how reviewer star ratings impact reader engagement, particularly through thumbs-up reactions. By analyzing the influence of emotional expressions in user-generated content on review scores and subsequent reader engagement, we seek to provide insights into their complex interplay. Our methodology employs advanced machine learning techniques to uncover subtle emotional nuances within user-generated content, offering novel insights into their relationship. The findings reveal an inverse correlation between review length and positive sentiment, emphasizing the importance of concise feedback. Additionally, the study highlights the differential impact of emotional tones on review scores and reader engagement metrics. Surprisingly, user-assigned ratings negatively affect reader engagement, suggesting potential disparities between perceived quality and reader preferences. In summary, this study pioneers the use of advanced machine learning techniques to unravel the complex relationship between emotional cues in customer evaluations, normative ratings, and subsequent reader engagement within the food delivery app context.

Static atomic charges affect key ground-state parameters of boron quasi-planar clusters Bn, n ≤ 20, which serve as building blocks of borophenes and other two-dimensional boron-based materials promising for various advanced applications. Assuming that the outer valence shells partial electron density of the constituent B atoms are shared between them proportionally to their coordination numbers, the static atomic charges in small boron planar clusters in the electrically neutral and positively and negatively singly charged states are estimated to be in the ranges of –0.750e (B70) to +0.535e (B200), –0.500e (B7+, B8+, and B9+) to +0.556e (B17+), and –1.000e (B7–) to +0.512e (B20–), respectively.

Infrastructure decision-making has traditionally been focused on the use of cost-benefit analysis (CBA) and multicriteria decision analysis (MCDA). Nevertheless, there remains no consensus in the infrastructure sector regarding a favored approach that comprehensively integrates resilience principles with those tools. This review focuses on how resilience has been evaluated in infrastructure projects. Initially, 400 papers were sourced from Web of Science and Scopus. After a preliminary review, 103 papers were selected, and ultimately, the focus was narrowed down to 56 papers. The primary aim was to uncover limitations in both CBA and MCDA, exploring various strategies for amalgamating them and enhancing their potential to foster resilience, sustainability, and other infrastructure performance aspects. Results were classified based on different rationalities: i) objectivist, ii) conformist, iii) adjustive, and iv) reflexive. The analysis revealed that while both CBA and MCDA contribute to decision-making, their perceived strengths and weaknesses differ depending on the chosen rationality. Nonetheless, embracing a broader perspective, fostering participatory methods, and potentially integrating both approaches seem to offer more promising avenues for assessing the resilience of infrastructures. The goal of this research proposal is to devise an integrated approach for evaluating the long-term sustainability and resilience of infrastructure projects and constructed assets.

As cities continue to face the increasing demands of urban transportation and the need for sustainable mobility solutions, the integration of intelligent transportation systems (ITS) with smart city infrastructure emerges as a promising approach. This paper presents a novel framework for integrating ITS with smart city infrastructure, aiming to address the challenges of urban transportation and promote sustainable mobility. The framework is developed through a comprehensive literature review, case studies, and stakeholder interviews, providing significant insights into the integration process. Our research outlines the key components of smart city infrastructure that can be integrated with ITS, highlights the benefits of integration, and identifies the challenges and barriers that need to be addressed. Additionally, we propose and apply evaluation methods to assess the effectiveness of ITS integration with smart city infrastructure. The results demonstrate the novelty and significance of this framework, as it significantly reduces traffic congestion, improves air quality, and enhances citizen satisfaction. This paper contributes to the existing literature by providing a comprehensive approach to integrating ITS with smart city infrastructure, offering a transformative solution for urban transportation challenges.

This study aims to determine the level of satisfaction of business actors with halal certification services by the Halal Product Assurance Organizing Agency (BPJPH), the only Indonesian government-owned agency for halal certification. This study uses a mixed method (quantitative-qualitative), with data collected using questionnaires involving 2367 respondents. The overall quality of certification services was evaluated using key dimensions from the perspective of the Service Quality Model (SERVQUAL), such as (1) certification requirements, (2) information and procedures, (3) completion time, (4) costs/tariffs, (5) service products, (6) competencies of executors, (7) executor behavior, (8) complaint handling, and (9) suggestions and inputs. Data were analyzed using descriptive analysis and the analysis of the weighted average of each dimension of satisfaction with the quality of public services. This study revealed that the overall satisfaction level of business actors was 84.86 (0–100). Among the nine indicators measured, eight fall within the “good” category (above 80.19); one indicator, i.e., the processing time of halal certification, was rated unsatisfactory (76.45); and none was classified as “very good.” The service gap between business actors’ expectations and BPJPH’s service delivery indicates the need to improve halal certification services. These include improvement in completion time, the executive’s behavior, costs, infrastructure, and information and procedures to streamline the certification process. The application of the SERVQUAL model in assessing halal certification standards in this study highlights the specific dimensions of service quality and the performance gaps, suggesting the need for continuous improvement to meet customer expectations effectively. This study examines halal certification services from BPJPH based on inputs from a large sample of Indonesian companies.